Tria Federal (Tria)Remote
Senior AI Engineer - Data Scientist
United States of America
Full Time
4 weeks ago
No H1B
Key skills
Large Language Models (LLMs)Generative AI (GenAI)Prompt EngineeringRetrieval-Augmented Generation (RAG) ArchitectureLLMOps PracticesOntology DesignKnowledge Graph DevelopmentPythonSQL (Snowflake SQL)DatabricksSnowflakeAWS Cloud ServicesCI/CD WorkflowsScaled Agile Framework (SAFe)SQLAIMLGenAILLMRAGLangChainLlamaIndexAgenticHugging FaceMLflowAnalyticsAWSTerraformKubernetesDockerJenkinsGitHub ActionsBedrockNeo4jPrometheusGrafanaGitHubAgileCI/CDA/B TestingCommunication
About this role
Tria Federal delivers digital services and technology solutions that support the health and safety of veterans, service members, and civilians. They are seeking a Senior AI Engineer / Data Scientist to lead the design, deployment, and scaling of enterprise AI capabilities, focusing on large language model solutions and healthcare ontology development.
Responsibilities:
- Design and maintain a healthcare ontology to normalize CMS data across claims, providers, and workflows
- Build and manage knowledge graphs (RDF/OWL or property graph) to support semantic search, inference, and RAG augmentation
- Develop graph data pipelines for ingestion, transformation, and entity resolution aligned with governance standards
- Collaborate with SMEs to define controlled vocabularies and create reusable semantic APIs for analytics and AI
- Architect and operationalize LLMs for production use cases including RAG, agentic workflows, and MCP tools
- Build LLM evaluation and safety frameworks (prompt quality, grounding, hallucination detection, bias checks) with automated testing and human-in-the-loop reviews
- Design cost- and latency-aware pipelines with observability for performance and reliability
- Implement LLMOps best practices: prompt versioning, CI/CD for artifacts, rollout strategies, and A/B testing
- Integrate vector databases and optimize chunking, embeddings, and retrieval for high-quality responses
- Support productionalization of AI/ML workflows with automated quality checks and lifecycle orchestration
- Ensure data security, governance, and CMS compliance
- Contribute to high-level system design for integrating new AI capabilities into a cloud-based analytics platform
- Maintain documentation and acceptance criteria for system changes
Requirements:
- 10+ years with BS/BA; 8+ years with MS/MA; 5+ years with PhD in Computer Science, Data Science, or related field
- Hands-on experience with LLMs and GenAI solutions, including prompt engineering, RAG architecture, and LLMOps practices
- Proven experience in ontology design and knowledge graph development for complex data-driven systems
- Experience with Databricks, Snowflake, and AWS Cloud Services
- Proficiency in Python and SQL (Snowflake SQL)
- Experience with CI/CD workflows and automated deployments
- Familiarity with Scaled Agile Framework (SAFe)
- Excellent communication skills and ability to work independently
- US Citizenship required
- Experience with Databricks E2 components (Unity Catalog, Feature Store)
- Knowledge of CMS systems and Medicare/Medicaid data
- Familiarity with LLM/GenAI tooling (LangChain, LlamaIndex, Hugging Face, AWS Bedrock)
- Experience with vector databases and RAG orchestration
- Knowledge graph tools: Neo4j, TigerGraph, AWS Neptune, RDF/OWL, SPARQL, Gremlin, Cypher, Protégé
- Model lifecycle & governance: MLflow, Model Registry, feature stores, LLM safety testing
- Observability & automation: GitHub Actions/Jenkins, Terraform, Docker/Kubernetes, Prometheus/Grafana